Enhanced Template-Based Voting Logic for Dual Train Detection Systems with Integrated Self-Diagnostics and Multiple-Component Fault Tolerance

A train detection system is vital for railway operations and safety, as the braking distance exceeds sight distance. Detection errors can result in signaling deficiencies and potential collisions, such as the near-miss incident at Jiadong station on August 28, 2019. Taiwan Railway employs a fixed-block signaling system with two axle counter subsystems within each block. Discrepancies between these detection systems present challenges for accurate train detection. Various decision logics have been implemented: a serial connection meets fail-safe requirements but reduces efficiency, a parallel connection enhances reliability but compromises safety, and a primary-secondary configuration can lead to underutilized systems. This study proposes an Enhanced Template-Based Voting Logic (ETVL) for dual train detection systems to fully leverage self-diagnosis capabilities and address multiple simultaneous component failures, along with an automatic evaluation platform to assess safety and reliability under these conditions. ETVL employs a Template Construction Module to create comprehensive templates of all possible occupancy statuses by simulating trains passing through the corresponding track, including both normal and failure scenarios. The Occupancy Matching Module then matches real-world occupancy statuses with the preconstructed templates and information from the self-diagnosis system. Case study results demonstrate that ETVL outperforms existing logics in terms of reliability and safety. Implementing this logic can significantly enhance the reliability and safety of dual train detection systems.